Abstract

This paper presents a new methodology developed to quantitatively analyze and prioritize the contributions of Human Factors (HFs) in the human-machine-interaction (HMI) within a complex sociotechnical system such as a Ballast Water Management (BWM) System. The methodology is a combination of the Human Factor Analysis Classification System (HFACS), Analytic Hierarchy Process (AHP), and a modified version of the Theory of Inventive Problem Solving (TRIZ) known as the Radial Dynamics Model (RDM). The methodology (HFACS-AHP-RDM) is based on a five-step algorithm, with which data from experts’ judgment was analyzed. A human-error and system risk minimization hierarchy was subsequently proposed to improve human performance and minimize the likelihood of an unwanted event such as the discharge of harmful aquatic organisms and pathogens (HAOPs). The result from the study in order of hierarchy showed fatigue, training and complex automation to be the HFs with the greatest impacts on BWM operations. Minimizing their impact, therefore, will have the greatest positive contribution on the performance of the system. Relevance to industryThe study's outcome shall help decision makers in prioritizing limited resources (e.g. time and money) allocation to resolving only issues related to HFs with the greatest impact on BWM System's performance. The new methodology could also be applicable in assessing the relative impacts of subjective criteria like HFs in complex sociotechnical systems other than BWM Systems.

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